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<title>Fast Artificial Neural Network Library (fann)</title>
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<div align="center"><b><big><big><big>Fast Artificial Neural Network Library (fann)</big></big></big></b></div>
<br>

<p>Fast Artificial Neural Network Library implements multilayer
artificial neural networks in C with support for both fully connected
and sparsely connected networks. Cross-platform execution in both
fixed and floating point are supported. It includes a framework for
easy handling of training data sets. It is easy to use, versatile,
well documented, and fast. PHP, Python, Delphi and Mathematica bindings are available.

<p align='center'><img src='BesselAll.gif'>

<p>A <a href='reference/index.html'>reference manual</a> accompanies the library with examples and
recommendations on how to use the library.

<p><b><big>Features for version 1.2.0:</big></b>
<ul>
  <li>Multilayer Artificial Neural Network Library in C
  <li>Backpropagation training (RPROP, Quickprop, Batch, Incremental)
  <li>Easy to use (create, train and run an ANN with just three function calls)
  <li>Fast (up to 150 times faster execution than other libraries)
  <li>Versatile (possible to adjust many parameters and features on-the-fly)
  <li>Well documented (An easy to use <a href='fann.html'>reference manual</a>, a 50+ page <a href='http://prdownloads.sourceforge.net/fann/fann_doc_complete_1.0.pdf?download'>university report</a> describing the implementation considerations etc. and an introduction <a href='fann_en.pdf'>article</a>)
  <li>Cross-platform (configure script for linux and unix, dll files for windows, project files for MSVC++ and Borland compilers are also reported to work)
  <li>Several different activation functions implemented (including stepwise linear functions for that extra bit of speed)
  <li>Easy to save and load entire ANNs
  <li>Several easy to use examples (simple <a href='http://cvs.sourceforge.net/viewcvs.py/fann/fann/examples/simple_train.c?view=markup'>train example</a> and simple <a href='http://cvs.sourceforge.net/viewcvs.py/fann/fann/examples/simple_test.c?view=markup'>test example</a>)
  <li>Can use both floating point and fixed point numbers (actually both float, double and int are available)
  <li>Cache optimized (for that extra bit of speed)
  <li>Open source (licenced under <a href='http://www.gnu.org/copyleft/lesser.html'>LGPL</a>)
  <li>Framework for easy handling of training data sets
  <li><a href='http://www.geocities.com/freegoldbar/indexExplorer.html'>Graphical Interface</a>
  <li><a href='http://www.geocities.com/freegoldbar/CppWrapperHelp/index.html'>C++ Bindings</a>
  <li><a href='fann.html#php'>PHP Extension</a>
  <li><a href='fann.html#python'>Python Bindings</a>
  <li><a href='fann.html#delphi'>Delphi Bindings</a>
  <li><a href='http://www.geocities.com/freegoldbar/indexExplorer.html'>.NET Bindings</a>
  <li><a href='http://www.geocities.com/freegoldbar/indexMath.html'>Mathematica Extension</a>
  <li><a href='http://blueruby.mydns.jp/fann/index.rbx?cmd=view;name=top'>Ruby Bindings</a>
  <li><a href='http://sourceforge.net/project/showfiles.php?group_id=93562'>RPM package</a>
  <li><a href='http://sourceforge.net/project/showfiles.php?group_id=93562'>Debian package</a>
</ul>

<br><i>Last updated Feb 15, 2005</i>

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